DLOIRCE

DLOIRCE

The aim of the project is to develop an autonomous system capable of real time object detection and recognition. The system should also be able to generate volumetric reconstructions about the objects it recognises. This capability is required to make the process of nuclear decommisioning more efficient, since the facilities that the proposed system will be used in are typically difficult to access and are currently inspected manually or by teleoperated machines. Automating this process reduces the hazard to human life while making the process a lot faster. The project will focus on developing the volumetric reconstruction capabilities of the system using low cost depth sensing devices, while utilising state-of-the-art techniques for object detection. Current reconstruction and inference techniques are primarily based on using information from 2D cameras which does not provide actual geometric information about the detected objects. Some approaches use a multi-view paradigm which, though useful, is not always possible, especially for inaccessible environments.

KEY FEATURES

TITLE

Deep Learning for Object Identification and Recognition in Challenging Environments

[DLOIRCE]

PROJECT TYPE

PHD

FUNDER

The University of Manchester

DATE

Sep 2016 - Sep 2019

ANANYA GUPTA BEng

Doctoral Research Student

Ananya is a President's Doctoral Scholar at the University of Manchester working on computer vision and robotics for her PhD. She did her undergraduate degree in Electronic Engineering at the University of Manchester and was a recipient of the prestigious Google Anita Borg Scholarship(2014). She has previously worked at Intel Corporation in the Internet of Things team as an engineer and feels passionate about involving more young students in Engineering

D45 Sackville, University of Manchester, Manchester, UK

ananya.gupta@manchester.ac.uk

 

OFFICE

EMAIL

Developing the next generation of nuclear decommissionning robotics research. Working in partnership with the nuclear sector and other unverisities around the UK and EU to reduce risk, accelerate productivity an reduce long term costs .

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School of Electrical and Electronic Engineering,

The University of Manchester, Sackville Street Building, Manchester, M13 9PL

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